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Record W2963380471 · doi:10.1089/humc.2018.201

The Landscape of Cellular and Gene Therapy Products: Authorization, Discontinuations, and Cost

2019· review· en· W2963380471 on OpenAlexaboutno aff
Vaishali Shukla, Enrique Seoane‐Vazquez, Souhiela Fawaz, Lawrence M. Brown, Rosa Rodríguez-Monguió

Bibliographic record

VenueHuman Gene Therapy Clinical Development · 2019
Typereview
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsAuthorizationCell therapyMedicineGenetic enhancementFood and drug administrationStem-cell therapyBusinessPharmacologyCellInternal medicineGeneBiologyComputer science

Abstract

fetched live from OpenAlex

Background: Cell and gene therapy products belong to a diverse class of biopharmaceuticals known as advanced therapy medicinal products. Cell and gene therapy products are used for the treatment and prevention of diseases that until recently were only managed chronically. The objective of this study was to examine the characteristics of market authorizations, discontinuations, and prices of cellular and gene therapy products worldwide. Data and Methods: We conducted an electronic search of authorized cell, tissue-engineered, and gene therapy products from the databases of the main drug regulatory agencies. The analysis excluded hematopoietic progenitor cell cord blood products authorized by the U.S. Food and Drug Administration. Price information was derived from the Red Book (Truven Health Analytics) for the United States, health technology assessment agencies for Europe, and other public sector sources and company news for other countries. We also searched the scientific literature for authorizations, discontinuations, and price information using MEDLINE/PubMed, Cochrane Library, Google Scholar, and EMBASE databases. All cost data were converted to U.S. dollars. Descriptive analysis was conducted in this study. Results: There were 52 different cell, tissue engineering and gene therapy products with 69 market authorizations in the world as of December 31, 2018. The products included 18 (34%) cell therapies, 23 (43.4%) tissue engineered products, and 12 (22.6%) gene therapies. There were 21 (30.4% of all authorizations) cell therapy, 26 (37.7%) tissue-engineered, and 22 (31.9%) gene therapy market authorizations. The EMA withdrew the authorization for two tissue engineering products, one cell therapy and one gene therapy, and New Zealand lapsed approval of one cell therapy. Most products were first authorized after 2010, including 10 (83.3%) gene therapies, 13 (72.2%) cell therapies, and 13 (56.5%) tissue-engineered products. The treatment price for four allogenic cell therapies varied from $2,150 in India to $200,000 in Canada. The treatment price for three autologous cell therapies ranged from $61,500 in the United Kingdom to a listed price of $169,206 in the United States. Tissue-engineered treatment prices varied from $400 in South Korea to $123,154 in Japan. Gene therapy treatment prices ranged from $5,501 for tonogenchoncel-L in South Korea to $1,398,321 for alipogene tiparvovec in Germany. Conclusions: A significant number of new cell, tissue, and gene therapies have been approved in the past decade. Most products were conditionally authorized and targeted rare cancers, genetic diseases, and other debilitating diseases. However, there are also products approved for cosmetic reasons. Cell, tissue, and gene therapies are among the most expensive therapies available. Healthcare systems are not prepared to assume the cost of future therapies for a myriad of rare diseases and common diseases of epidemic proportions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.016
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.206
GPT teacher head0.429
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations81
Published2019
Admission routes1
Has abstractyes

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